Advanced Information Processing Techniques Research Articles

Information in The Three Dimensions of Time

The relationship between physics and information processing is a topic of great significance in the realm of science and technology. The laws of physics, which govern the behavior of matter and energy, also have a profound influence on the way information is processed and utilized. While the mathematics governing information processing has not extensively utilized the laws of physics, it is evident that there is potential for these laws to play a more significant role, particularly in the context of quantum systems. based on the equivalence between information and energy, we can explore how other laws of physics can effectively contribute to more efficient and advanced information processing techniques. This research sheds light on the interconnectedness of physics and information processing, and its findings have the potential to significantly enhance our ability to process information, particularly in cutting-edge quantum systems. By recognizing and leveraging the influence of physics, we can pave the way for further advancements in information processing technologies.

Artificial intelligence-driven innovation for enhancing supply chain resilience and performance under the effect of supply chain dynamism: an empirical investigation.

Supply chain resilience (SCRes) and performance have become increasingly important in the wake of the recent supply chain disruptions caused by subsequent pandemics and crisis. Besides, the context of digitalization, integration, and globalization of the supply chain has raised an increasing awareness of advanced information processing techniques such as Artificial Intelligence (AI) in building SCRes and improving supply chain performance (SCP). The present study investigates the direct and indirect effects of AI, SCRes, and SCP under a context of dynamism and uncertainty of the supply chain. In doing so, we have conceptualized the use of AI in the supply chain on the organizational information processing theory (OIPT). The developed framework was evaluated using a structural equation modeling (SEM) approach. Survey data was collected from 279 firms representing different sizes, operating in various sectors, and countries. Our findings suggest that while AI has a direct impact on SCP in the short-term, it is recommended to exploit its information processing capabilities to build SCRes for long-lasting SCP. This study is among the first to provide empirical evidence on maximizing the benefits of AI capabilities to generate sustained SCP. The study could be further extended using a longitudinal investigation to explore more facets of the phenomenon.

Neural network based design of metagratings

Metagratings are flat and thin surfaces that rely on unique, periodically repeating (non-gradient), arbitrary shaped light scattering units for wave manipulation. However, the absence of an empirical relationship between the structural and diffraction properties of the units enforces utilization of brute force numerical optimization techniques to determine the unit shape for a desired application. Here, we present an artificial neural network based methodology to develop a fast-paced numerical relationship between the two. We demonstrate the training and the performance of a numerical function, utilizing simulated diffraction efficiencies of a large set of units, that can instantaneously mimic the optical response of any other arbitrary shaped unit of the same class. We validate the performance of the trained neural network on a previously unseen set of test samples and discuss the statistical significance. We then utilize the virtually instantaneous network operations to inverse design the metagrating unit shapes for a desired diffraction efficiency distribution. The proposed inter-disciplinary combination of advanced information processing techniques with Maxwell's equation solvers opens a pathway for the fast-paced prediction of metagrating designs rather than full wave computation.

SU-GG-T-264: An Infrastructure Towards Better and Safer Radiation Therapy-Quality Assurance Information System (QAIS)

Purpose: To develop an infrastructure to perform digital, automatic, intelligent, process‐oriented, and patient safety‐oriented quality control in radiation oncology. To leverage an electronic infrastructure to use advanced information processing techniques, proactive quality control tools, employ automated and intelligent systems and facilitate standardization, data sharing & benchmarking in radiation oncologyquality control program Method: An web based centralized data management system called Mallinckrodt Institute of Radiology Quality AssuranceInformation System ( MIR‐QAIS) was developed to collect manage and analyzequality assurance data. Several tools that could leverage the electronic environment was developed such as automated quality control for patient specific IMRT delivery, electronic chart checking, workflow monitor and manager, status reporting with dashboards, calculation based quality assurance,data mining tools for data informatics, document management component, incident reporting for organizational learning etc. This infrastructure has facilitated us to go completely paperless including all quality assurance tasks. Also all the test that are in developed is to perform quality control rather than quality assurance. The infrastructure was designed for easy record keeping, auditing, and compliance and to facilitate standardization and benchmarking. Results: We have developed a web based infrastructure to practice quality control in radiation oncology. Several tools were developed leveraging this infrastructure. Web‐based QA documents for Machine QA with statistical analysis tools, alerts and warnings, Dynalog based automated patient specific QA, Electronic chart check, automatic QA plan generation through scripts, intelligent review of plan quality, technical aspects of plan and logical consistency using scripts are to name a few. Conclusion: The electronic web based QAIS infrastructure has facilitated and would continue to aid in developing effective quality control program to practice better and safer radiation therapy.

An Intelligent IN

The Intelligent Network [IN] is a network concept to ease the introduction of new services based on more flexibility and new capabilities. This paper describes an evolution towards a more intelligent structure provided by Advanced Information Processing techniques with emphasis on a Distributed Artificial Intelligence concept.

Service and traffic management for IBCN

The future Integrated Broadband Communications Network (IBCN) will provide high-speed communication capabilities that support a variety of existing and new services. The management of such a complex environment requires innovative management systems. NEMESYS is a project within the European Commission's Research and Development in Advanced Communications in Europe (RACE) program. The project goals are to demonstrate and evaluate the use of advanced information processing techniques for quality-of-service and traffic management. To reach these goals, a series of experimental prototypes are being built. This paper describes the assumptions, objectives, and approach of NEMESYS, and in particular, the design and implementation of an experiment that investigates service and traffic management techniques in a simulated asynchronous transfer mode environment. Because the project is not yet finished, some preliminary results are presented.

Genetic determination of the human EEG. Survey of recent results on twins reared together and apart.

In this article, we have discussed recent progress in quantifying the genetically determined component of the resting EEG. This progress has been made possible in particular by the application of advanced information processing techniques such as "supervised learning," and the development of a problem-oriented "similarity" concept. Our work aimed at modeling previous findings regarding the distinct individuality of human brain-wave patterns, the high similarity between the EEGs of monozygotic twins, and the average within-pair similarity of dizygotic twins. Thus, we had three objectives: First, we wanted to improve the quantification of EEG characteristics with respect to reproducibility and specificity by means of adaptive procedures and repeated measurements. Second, we wanted to compare the "typical" within-subject EEG similarity with the "typical" within-pair EEG similarity of monozygotic and dizygotic twins brought up together. Finally, we were interested in the degree to which environmental factors affect the characteristics of human brain-wave patterns. Our investigations were based on the empirical data derived from five different populations: (1) 81 healthy subjects, (2) 24 pairs of monozygotic twins brought up together, (3) 25 pairs of dizygotic twins brought up together, (4) 28 pairs of monozygotic twins reared apart, and (5) 21 pairs of dizygotic twins reared apart. Following our similarity conception, repeated measurements on the set of 81 individuals were used as design samples, and new registrations from the same individuals taken 14 days later were referred to as test samples in order to develop the appropriate method and to determine all required calibration parameters. This specific approach allowed us to construct EEG spectral patterns which, with a specificity and reproducibility of greater than 90% each, largely met the requirements of genetic EEG studies. Hence, we were able systematically to investigate the within-pair EEG similarity of our twin samples.(ABSTRACT TRUNCATED AT 400 WORDS)

The impact of advanced information processing on simulation — An illustrative review

Advanced Information Processing (AIP) techniques are felt to play an important role in next generation simulation tools. Here we will review and illustrate the incorporation of two such AIP techniques in modelling and simulation. Simulation-oriented information-base management systems are considered to auto matize one of the major activities, peripheral to large-scale modelling and model implementation : the management of the descriptive and quantitative data involved. On the other hand, attention is paid to the impact of artificial intelligence techniques in modelling and simulation. Knowledge-based simulation, Al supported model synthesis and some additional topics with respect to integrating Al and the system analysis approach are briefly reviewed. Some concepts are illustrated on the basis of research activities in the Benelux countries.